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pytorch-forecasting
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| DeepADoTS | pytorch-forecasting | |
|---|---|---|
| 1 | 9 | |
| 538 | 3,578 | |
| 0.0% | - | |
| 0.0 | 8.7 | |
| almost 2 years ago | 7 days ago | |
| Python | Python | |
| MIT License | MIT License |
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[D] Anomaly detection without training set?
Other than that, if you're looking for more complicated models you could try and adapt one of the models from this this GitHub repo for your task (this is an open source repo of some SOTA anomaly detection models).
pytorch-forecasting
- FLaNK Stack Weekly for 14 Aug 2023
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Pytorch Lstm
Source: Conversation with Bing, 4/5/2023 (1) jdb78/pytorch-forecasting: Time series forecasting with PyTorch - GitHub. https://github.com/jdb78/pytorch-forecasting. (2) Time Series Prediction with LSTM Using PyTorch - Colaboratory. https://colab.research.google.com/github/dlmacedo/starter-academic/blob/master/content/courses/deeplearning/notebooks/pytorch/Time_Series_Prediction_with_LSTM_Using_PyTorch.ipynb. (3) time-series-classification · GitHub Topics · GitHub. https://github.com/topics/time-series-classification. (4) PyTorch: Dataloader for time series task - Stack Overflow. https://stackoverflow.com/questions/57893415/pytorch-dataloader-for-time-series-task.
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[D] What is the best approach to create embeddings for time series with additional historical events to use with Transformers model?
Temporal fusion transformer https://github.com/jdb78/pytorch-forecasting
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LSTM/CNN architectures for time series forecasting[Discussion]
Pytorch-forecasting
- Can someone help me with this? It's been days that i struggle with this problem, Forecasting w DeepAR
- Can someone help me with this? it's been days that i struggle with this problem
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[P] Beware of false (FB-)Prophets: Introducing the fastest implementation of auto ARIMA [ever].
To name a few: https://github.com/jdb78/pytorch-forecasting, https://github.com/unit8co/darts, https://github.com/Nixtla/neuralforecast
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When to go for an 'easy' time-series model vs. using a complex deep learning model (when having experience with the latter)
I'm a data trainee at this organisation. I wrote my master thesis about using an event clustering mechanism to enrich an existing dataset to improve short-term demand predictions, using Pytorch Forecasting using the temporal fusion transformer component, and LightGBM (and compare the models with and w/o the event feature, so 4 runs in total).
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A python library for easy manipulation and forecasting of time series.
Darts is a pretty nice one. I've recently been using pytorch-forecasting for larger models like the Temporal Fusion Transformer. https://github.com/jdb78/pytorch-forecasting
What are some alternatives?
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
neural_prophet - NeuralProphet: A simple forecasting package
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
luminaire - Luminaire is a python package that provides ML driven solutions for monitoring time series data.
Lime-For-Time - Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
Informer2020 - The GitHub repository for the paper "Informer" accepted by AAAI 2021.
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
tslearn - The machine learning toolkit for time series analysis in Python
snntorch - Deep and online learning with spiking neural networks in Python